Cedat, D.: Modeling and Experiment on Mo-based high temperature composites. Dissertation, Ecole Centrale Paris, Laboratoire for Materials, Paris [France] (2008)
Sachs, C.: Microstructure and mechanical properties of the exoskeleton of the lobster Homarus americanus as an example of a biological composite material. Dissertation, RWTH Aachen, Aachen, Germany (2008)
Tjahjanto, D.: Micromechanical Modeling and Simulations of Tranformation-Induced Plasticity in Multiphase Carbon Steels. Dissertation, TU Delft, Delft, The Netherlands (2008)
Klüber, C.: Korrelation von mechanischen Eigenschaften und Kristallorientierung auf mikroskopischer und nanoskopischer Ebene. Dissertation, RWTH Aachen, Aachen, Germany (2008)
Bastos da Silva, A. F.: Characterization of the Microstructure, Grain Boundaries and Texture of Nanostructured Electrodeposited CoNi by use of EBSD. Dissertation, RWTH Aachen, Aachen, Germany (2007)
Goerdeler, M.: Application of a dislocation density based flow stress model in the integrative through-process modeling of Aluminium production. Dissertation, RWTH Aachen, Aachen, Germany (2007)
Wolff, C.: Der tribologisch asymmetrische Flachstauchversuch - Eine neue Methode zur Analyse von Reibungsvorgängen bei Umformprozessen. Dissertation, RWTH Aachen, Aachen, Germany (2001)
Kaushal, C.: Untersuchung der Abhängigkeit des Ölaustrags von der Oberflächenfeinstruktur beim Auswalzen gedoppelter Aluminiumfolien. Diploma, HS Niederrhein, Krefeld, Germany (2003)
Tranchant, J.: Deformation of Semi-Brittle Intermetallic Material under Superimposed Hydrostatic Pressure. Diploma, Ecole Centrale de Nantes, Nantes, France (2002)
Paiva do Nascimento, A. W.: An optimized method to determine initial parameters of advanced yield surfaces for sheet metal form-ing applications. Master, Ruhr-Universität Bochum (2021)
Kusampudi, N.: Using Machine Learning and Data-driven Approaches to Predict Damage Initiation in Dual-Phase Steels. Master, Ruhr-Universität Bochum (2020)
Soundararajan, C. K.: Recrystallization behavior and mechanical properties of interstitially alloyed CoCrFeMnNi equiatomic high entropy alloy. Master, RWTH Aachen University (2020)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.